Performance comparison of VVC, AV1, and HEVC on 8-bit and 10-bit content

Topiwala, Pankaj; Krishnan, Madhu; Dai, Wei

doi:10.1117/12.2322024

Cited by 21 publications

(12 citation statements)

References 5 publications

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“…Our anchor encoders comprise AVC/H.264, AV1 and VVC, utilizing the libx264, aomenc and vvenc open implementations of these standards. We deliberately focus on a very-highly optimized encoding setup that is known to outperform all neural or run-of-the-mill proprietary video encoders by a large margin [17,11,39,9]. Our aim is to examine if DPP can push the envelope of what is achievable today under some of the most-advanced encoding conditions used in practice.…”

Section: Experimental Setup For Bd-rate Resultsmentioning

confidence: 99%

“…While learned video compression has shown some promise for high-bitrate lowdelay video compression [23,2,3,12,34], standard codecs like AVC and HEVC surpass all current methods in learned video compression in terms of standard metrics like SSIM and VMAF when the former are used with all their advanced prediction and entropy coding tools enabled [11]. In addition, more advanced encoder designs of the AO-Media AV1 [14] and MPEG/ITU-T Versatile Video Coding (VVC) standards [39] now include neural components for optimized encoding tool selection [14]. Such standards allow for decoders on CPU-based commodity devices like tablets and mobile phones and there is no need for bespoke encoder or decoder components that require joint optimization, as in recent proposals [9,1].…”

Section: Compressionmentioning

confidence: 99%

See 1 more Smart Citation

Deep Perceptual Preprocessing for Video Coding

Chadha¹,

Andreopoulos²

2021

2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

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Section: Experimental Setup For Bd-rate Resultsmentioning

confidence: 99%

Section: Compressionmentioning

confidence: 99%

Deep Perceptual Preprocessing for Video Coding

Chadha¹,

Andreopoulos²

2021

2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

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“…For instance, HEVC which was introduced in 2013 shows 50% [147] coding efficiency improvement compared to its predecessor H.264. Similarly, VVC which was standardized in 2020 [148] demonstrates 30-35% [149], [150] bit rate reduction compared to HEVC for a similar video quality level. However, these improvements in the bit rate reduction arrive with a greater increase in the encoding complexity which demands a significant amount of computational and energy resources at the encoding servers/devices [150]- [152].…”

Section: B Impact Of the Encoder Optimization On Qoementioning

confidence: 99%

Measuring, Modeling and Integrating Time-Varying Video Quality in End-to-End Multimedia Service Delivery: A Review and Open Challenges

et al. 2022

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The multimedia delivery chain consists of multiple stages such as content preparation, content delivery via Over-The-Top delivery network and Internet Service Providers network. Within the multimedia service chain, each stage influences the Quality of Experience (QoE) of the end user. The objective of this work is to provide a comprehensive literature survey with future research challenges and opportunities in the field of time-varying video quality in multimedia service delivery. The contribution of this work is two fold: 1) Survey -we provide a review of state-of-the-art works for video quality models to quantify multiple artifacts into a single QoE metric, pooling strategies for global quality measurements, and Continuous Time-Varying Quality (CTVQ) models; 2) Future Challenges and Directions -we investigate ten major research challenges and future directions based on the state-of-the-art for QoE modelling, QoE-aware encoding/decoding and QoE monitoring/management of multimedia streaming in next-generation networks.

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“…Works in [12], [16] and [17] used informal MOS scores rather than MOS scores obtained from ITU-T recommended subjective test procedure.…”

Section: On-demandmentioning

confidence: 99%

User Generated HDR Gaming Video Streaming: Dataset, Codec Comparison and Challenges

Barman¹,

Martini²

2021

Preprint

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Gaming video streaming services have grown tremendously in the past few years, with higher resolutions, higher frame rates and HDR gaming videos getting increasingly adopted among the gaming community. Since gaming content as such is different from non-gaming content, it is imperative to evaluate the performance of the existing encoders to help understand the bandwidth requirements of such services, as well as further improve the compression efficiency of such encoders. Towards this end, we present in this paper GamingHDRVideoSET 1 , a dataset consisting of eighteen 10-bit UHD-HDR gaming videos and encoded video sequences using four different codecs, together with their objective evaluation results. The dataset is available online at [to be added after paper acceptance]. Additionally, the paper discusses the codec compression efficiency of most widely used practical encoders, i.e., x264 (H.264/AVC), x265 (H.265/HEVC) and libvpx (VP9), as well the recently proposed encoder libaom (AV1), on 10-bit, UHD-HDR content gaming content. Our results show that the latest compression standard AV1 results in the best compression efficiency, followed by HEVC, H.264, and VP9.

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Performance comparison of VVC, AV1, and HEVC on 8-bit and 10-bit content

Cited by 21 publications

References 5 publications

Deep Perceptual Preprocessing for Video Coding

Deep Perceptual Preprocessing for Video Coding

Measuring, Modeling and Integrating Time-Varying Video Quality in End-to-End Multimedia Service Delivery: A Review and Open Challenges

User Generated HDR Gaming Video Streaming: Dataset, Codec Comparison and Challenges

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